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Google: Gemma 4 31B vs OpenAI: GPT-5 Nano

Head-to-head API cost, context, and performance comparison. Synced at 10:28:28 PM.

Executive Summary

When evaluating Google: Gemma 4 31B against OpenAI: GPT-5 Nano, the pricing structure is a key differentiator. OpenAI: GPT-5 Nano is approximately 17% more cost-effective per 1 million tokens overall.

However, when looking at raw reasoning capabilities, Google: Gemma 4 31B leads with a statistical ELO score of 1583. For tasks involving complex logic, coding, or instruction-following, developers might prefer Google: Gemma 4 31B, provided their budget allows for the API burn rate.

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Raw Technical comparison

Metric
Google: Gemma 4 31B
OpenAI: GPT-5 Nano
Performance (ELO)
1583
1483
Input Cost / 1M
$0.14
$0.05
Output Cost / 1M
$0.40
$0.40
Context Window
262,144 tokens
400,000 tokens

Verdict

If you are looking for pure performance and capability, Google: Gemma 4 31B is statistically superior. However, if API burn rate is the primary concern, OpenAI: GPT-5 Nano wins out aggressively in pricing.

People Also Ask

Is Google: Gemma 4 31B cheaper than OpenAI: GPT-5 Nano?

No. OpenAI: GPT-5 Nano is the more cost-effective model, operating at a lower price point per 1 million tokens.

Which model has the larger context window?

The OpenAI: GPT-5 Nano model has the advantage in memory, offering a massive 400,000 token limit for document ingestion.

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